Statistical evidence presents a unique challenge in legal proceedings. Statistical evidence can provide weight for the prosecution's claim that a given suspect has committed a particular crime. Of particular concern here are instances in which a forensic examiner, or expert, has established a match between a piece of evidence found at the crime scene and a corresponding piece of evidence directly related to the suspect him or herself—for example, a crime scene image of a perpetrator in a unique set of clothing, and similar if not identical clothing being found to belong to the suspect. Even if such a match is incontrovertible, the match may still be accidental.
Historically, a match is presented only if it could be reasonably assumed that the probability of accidental match is zero. For example, fingerprint evidence would only be admissible if enough features are observed in the crime scene evidence to preclude any individual other than the suspect having left the fingerprints. However, modern forensic science has generally recognized that such certainty can never truly be attained except in a very small number of situations.
In some criminal investigations, critical pieces of evidence include surveillance images showing the perpetrator of a crime wearing clothing that can be matched to clothing worn or owned by a suspect. Experts can, in some cases, find and document matching areas between the clothing depicted in these images to the clothing obtained from the suspect, and this evidence is specific enough so as to constitute proof. These matches, however, can be imperfect for a number of reasons, such as poor surveillance image quality, inherent repetition of the garment manufacturing process leading to garments having similar visual appearance, and so on. Thus, it is important for forensic examiners, judges, juries, and others to understand the quality of the match. Statistically analyzing these garment matches can provide quantitative information on match quality. Unfortunately, general garments are usually highly varied, and in many cases not enough is known about them to estimate meaningful statistics that can be used at trial.